A Cooperative Game Framework for Bandwidth Allocation in 4G Heterogeneous Wireless Networks
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Bibliographic record
Abstract
One of the most important features of the evolving fourth generation (4G) wireless networks is the capability of a mobile station to connect to several wireless access networks simultaneously. This introduces new challenges in bandwidth allocation among mobiles since the load characteristics of different networks must be taken into account to design efficient resource allocation algorithms. In this paper, we present bandwidth allocation and admission control algorithms based on bankruptcy game which is a special type of an N-person cooperative game. A coalition among the different wireless access networks is formed to offer bandwidth to a new connection. The stability of the allocation is analyzed by using the concept of the core and the amount of allocated bandwidth to a connection in each network is obtained by using Shapley value. Subsequently, an admission control algorithm is proposed. Numerical results are presented to demonstrate the behaviors of the proposed algorithms.
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Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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